中国科学院心理研究所机构知识库

通过移动无人机(UAV)收集无线传感网络数据的方案已受到广泛关注,将感测的数据与产生此数据的传感节点位置关联起来是十分必要的。为此提出了基于无人机的强健节点定位算法(UAV-NL)。UAV-NL算法将UAV位置作为未知信息。传感节点接收由UAV在随机位置传输的beacon包,并记录接收信号强度指示(RSSI)矢量;通过理论推导2个RSSI矢量的范数距离与这2节点距离的线性关系;最后,通过RSSI值测距,并利用半定规划(SDP)算法估计节点位置。仿真结果表明,提出的UAV-NL算法即使在噪声信道条件下仍具有高的定位精确度。

The use of mobile Unmanned Aerial Vehicle(DAV) to collect data from Wireless Sensor Networks(WSNs) has attracted great attention recently. It is often necessary to relate the stream of sensed data to the deployed location of the data producing sensor nodes. Therefore, UAV-based Robust Node Localization(UAV-NL) algorithm is proposed. In UAV-NL algorithm, the location of UAV is unknown. Each sensor node receives beacon packets transmitted by the UAV at random positions and records an Received Signal Strength Indicator(RSSI) vector. The norm distance of two RSSI vectors, which is theoretically proved to be linearly related to the distance between two nodes, is used for ranging. Distance calculation method is theoretically derived by using RSSI measurements. Location of node is estimated by Semi-Definite Programming(SDP) algorithm. Extensive simulations in different environments validate high localization accuracy of the proposed algorithm even under noisy channel conditions.

河南省科技攻关资助项目(182102210599)